Incentive framework for mobile data offloading market under QoE‐aware users

Song, Xin; Qin, Lei; Qi, Haoyang; Li, Suyuan; Hai-jun, Qian; Li, Dong; Ni, Yue

doi:10.1049/iet-com.2019.0498

Cited by 7 publications

(2 citation statements)

References 29 publications

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“…In [47], the author considers the cellular traffic overload issue. The author proposed an incentive-based scheme using the Stackelberg three-stage model that improves the user satisfaction level without affecting the MNO revenue.…”

Section: Related Workmentioning

confidence: 99%

Stackelberg game for heterogeneous traffics management in next‐generation cellular network

Asif

Ghani-Ur-Rehman

Zubair³

et al. 2021

IET Communications

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The innovations in the internet of things and the advent of media-intensive applications have massively increased the data burden on third-and fourth-generation (wireless cellular technology) mobile networks. The existing cellular networks face an overloading issue due to the growing rate of data traffics resultantly reducing the quality of service (QoS) in terms of delay and throughput. To overcome this issue, mobile network operators are searching for well-organized ways to support such a massive data flow. Mobile data offloading schemes through small cells such as WiFi can be implemented to provide a lucrative and effective solution. A game-based quality of service model for heterogeneous traffic to achieve the quality of service parameters is proposed. This model deals with a trade-off between mobile network operators and access points, allocating economic incentives by mobile network operators to acess points for saving the spectrum. The model is simulated in MATLAB and the preliminary analyses proved the intense impact of the model on the offloading ratio and energy consumption by achieving superior results in the aforementioned parameters.

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Section: Related Workmentioning

confidence: 99%

Stackelberg game for heterogeneous traffics management in next‐generation cellular network

Asif

Ghani-Ur-Rehman

Zubair³

et al. 2021

IET Communications

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“…A detailed survey on mobile data offloading can be found in Rebecchi et al [3] and Zhou et al [12] and references therein. Literature on the problem of mobile data offloading can be classified based on (1) the system model, ( 2) system parameters, (3) performance metrics, and (4) the analytical framework adopted, such as game theory [13][14][15], optimization [16][17][18][19], artificial intelligence/learning-based methods [20,21], and stochastic/queuing theory-based methods [9,[23][24][25]. Table 1 provides the classification of some of the literature in the area of mobile data offloading.…”

Section: Literature Surveymentioning

confidence: 99%

Delayed mobile data offloading scheme for quality of service traffic: Design and analysis

Ajith

Venkatesh

2021

IET Networks

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As the world is entering the era of 5G, we are witnessing exponential growth in the volume of data traffic generated and consumed by mobile devices. Mobile data offloading handles the surge in mobile data traffic by offloading part of the traffic onto the Wi-Fi network. In this context, we design and analyse a quality of service (QoS) enhancement scheme for delayed mobile data offloading. We first consider prioritised queuing of traffic as a scheme for QoS provisioning. Using the concepts of virtual waiting time, renewal process, and level crossing arguments, we derive the average transmission delay of the offloaded and reneged packets of high priority. Next, we mathematically validate the benefit of balking all such packets whose expected virtual waiting time exceeds their deadline. Using a three-dimensional Markov chain model, we derive the required balking probability. Moreover, we merge the technique of balking with prioritisation for improving QoS in delayed offloading. Through an extensive simulation, we validate our analysis and demonstrate how the proposed scheme reduces the transmission delay without sacrificing offloading efficiency. Our investigation has the potential to be adopted in future mobile data offloading standards for improving QoS.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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